DocumentCode :
2721692
Title :
Thermal generation planning strategy facilitating units decomposition by particle swarm optimization and multi-stage dynamic programming
Author :
Chakraborty, Shantanu ; Senjyu, Tomonobu ; Yona, Atsushi ; Saber, Ahmed Yousuf ; Funabashi, Toshihisa
Author_Institution :
Dept. of Electr. & Electron. Eng., Univ. of the Ryukyus, Nishihara, Japan
fYear :
2009
fDate :
26-30 Oct. 2009
Firstpage :
1
Lastpage :
4
Abstract :
This paper presents a methodology for determining optimal generation schedule for thermal units by using a combined approach of particle swarm optimization (PSO) and dynamic programming (DP). At first, the units are decomposed into several hours based on the forecasted load demand. Then unit commitment (UC) problem is solved for each single hour using binary version of PSO. While solving hourly UC, the decoupled constraints such as system power balance, system spinning reserve are considered. A number of better solutions are stored for each hour which will be applied generating the multi stage graph for merging procedure. Then the decomposed hourly units´ schedules are merged to produce the final solution. For merging procedure, this method applies multi-stage dynamic programming approach. Coupling constraints such as ramp rate, minimum up/down time constraint are integrated with that DP approach. The simulation results show the effectiveness of this algorithm by comparing the outcome with several established methods.
Keywords :
dynamic programming; particle swarm optimisation; power generation planning; power generation scheduling; thermal power stations; Coupling constraints; load demand; minimum up-down time constraint; multistage dynamic programming; multistage graph; optimal generation schedule; particle swarm optimization; ramp rate; system power balance; system spinning reserve; thermal generation planning strategy; unit commitment problem; units decomposition; Demand forecasting; Dynamic programming; Dynamic scheduling; Load forecasting; Merging; Particle swarm optimization; Spinning; Strategic planning; Thermal decomposition; Time factors; Multi Stage Dynamic Programming; Particle Swarm Optimization; Unit Commitment;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Transmission & Distribution Conference & Exposition: Asia and Pacific, 2009
Conference_Location :
Seoul
Print_ISBN :
978-1-4244-5230-9
Electronic_ISBN :
978-1-4244-5230-9
Type :
conf
DOI :
10.1109/TD-ASIA.2009.5357010
Filename :
5357010
Link To Document :
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